Triple

T193876
Position Surface form Disambiguated ID Type / Status
Subject Nadezhda Alliluyeva E3776 entity
Predicate placeOfDeath P21 FINISHED
Object Moscow E1747 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Moscow | Statement: [Nadezhda Alliluyeva, placeOfDeath, Moscow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow
Context triple: [Nadezhda Alliluyeva, placeOfDeath, Moscow]
  • A. Moscow chosen
    Moscow is the capital and largest city of Russia, serving as its political, economic, and cultural center.
  • B. Yekaterinburg
    Yekaterinburg is a major industrial and cultural city in Russia’s Ural region, historically known as the site of the execution of the last Russian tsar, Nicholas II, and his family.
  • C. Kazan
    Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
  • D. Nizhny Novgorod
    Nizhny Novgorod is a major Russian city located at the confluence of the Volga and Oka rivers, known for its historic Kremlin, industrial significance, and role as a key cultural and economic center in the Volga region.
  • E. Rostov-on-Don
    Rostov-on-Don is a major port city in southern Russia, located on the Don River near the Sea of Azov and serving as an important administrative, cultural, and industrial center of the region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a2548debd48190ae3a06d6e65b53c6 completed Feb. 28, 2026, 2:35 a.m.
NER Named-entity recognition batch_69a2596810c48190ab687c0c2efaa9e2 completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3b46e24888190b400bf5ee8028e7c completed March 1, 2026, 3:37 a.m.
Created at: Feb. 28, 2026, 2:41 a.m.